Importance of suppression and mitigation measures in managing COVID-19 outbreaks

Michael E. Hochberg

The second variable explored was the effectiveness of previous suppression measures; we evaluated high effectiveness (a reset to a single infectious case) and a less, but still acceptable reset to 100 infectious cases. Clearly, any subsequent mitigation measures yielding â„›C<1.0 would result in infectious cases decreasing over time (and therefore be a successful outcome), but given the impacts of such measures on society, below we consider strategies that seek to contain a second epidemic by tuning â„›C to between 1.0 and â„›0. the infectious numbers to less than 10% of the total population requires â„›C less than c.1. 5 , which is about a 40% reduction in the â„›0 assumed here ( Fig. 2A) . Peak levels of hospitalization can reach c.7%-10% should mitigation measures be 20% or less effective at reducing â„›0 (Fig. 2B) . Such levels would exceed hospital bed capacity in most countries by at least an order of magnitude (18). Reducing peak hospitalization levels well below 1% (which is still too high for many health services) would require â„›C close to 1.0. Finally, similar to the trends in Figs. 2A,B , fatalities are sensitive to the effectiveness of prior suppression measures and community size, indicating that â„›C needs to be reduced towards unity for smaller communities and those unable to reduce infectious cases sufficiently during suppression measures (Fig. 2C) . These results emphasize that epidemics could be contained by tuning â„›C close to, but above 1.0, which would be more logistically and socially attainable than â„›C<1.0.